Generally, people do various things while walking. For example, people frequently walk while looking at their smartphones. Sometimes we walk differently than usual; for example, when walking on ice or snow, we tend to waddle. Understanding walking pa...
24 January 2022
People who exercise may benefit or be injured depending on their foot striking (FS) style. In this study, we propose an intelligent system that can recognize subtle differences in FS patterns while walking and running using measurements from a wearab...
In this paper, we propose an integrated action classification and regression learning framework for the fine-grained human action quality assessment of RGB videos. On the basis of 2D skeleton data obtained per frame of RGB video sequences, we present...
The proportion of the aging population is rapidly increasing around the world, which will cause stress on society and healthcare systems. In recent years, advances in technology have created new opportunities for automatic activities of daily living...
(1) Background: Soccer action recognition (SAR) is essential in modern sports analytics, supporting automated performance evaluation, tactical strategy analysis, and detailed player behavior modeling. Although recent advances in deep learning and com...
Millimeter-wave (mmWave) radar-based gesture recognition has attracted increasing attention for real-time human–computer interaction owing to its robustness to illumination changes, privacy-preserving sensing capability, and suitability for emb...
The squat is a multi-joint exercise widely used for everyday at-home fitness. Focusing on the fine-grained classification of squat motions, we propose a smartwatch-based wearable system that can recognize subtle motion differences. For data collectio...
To address the issue of decreased localization accuracy and robustness in existing visual SLAM systems caused by imprecise identification of dynamic regions in complex dynamic scenes—leading to dynamic interference or reduction in valid static...
This study investigates how Chinese learners of English express manners of motion, examining systematic features, cognitive motivations, and compensatory strategies. While Talmy’s motion events typology and Levin’s verb classification sys...
Skeleton-based action recognition has attracted considerable research interest because skeleton data are inherently robust to illumination changes, viewpoint variation, background clutter, and camera motion. Nevertheless, extracting informative repre...
High-dynamic amusement ride conditions involving impacts, rapid rotations, and abrupt posture changes introduce severe motion artifacts that degrade vital sign quality and destabilize physiological state recognition. This study aims to develop an eng...
Apple leaf disease identification with high precision is one of the main challenges in precision agriculture. The datasets usually have class imbalance problems and environmental changes, which negatively impact deep learning approaches. In this pape...
Exoskeleton robots function as augmentation systems that establish mechanical couplings with the human body, substantially enhancing the wearer’s biomechanical capabilities through assistive torques. We introduce a lumbar spine-assisted exoskel...
Human pose comparison involves measuring the similarities in body postures between individuals to understand movement patterns and interactions, yet existing methods are often insufficiently robust and flexible. In this paper, we propose a RotJoint-b...
Human activity recognition in privacy-sensitive indoor environments requires sensing modalities that remain robust under illumination variation and background clutter while preserving user anonymity. To this end, this study proposes a lightweight rad...
This paper presents a multimodal sensing approach for fine-grained soccer action recognition using synchronized mm-wave FMCW radar and multiview RGB cameras. A TI IWR1443BOOST FMCW radar and three Sony IMX296 global-shutter cameras were used to recor...
Sign Language Recognition (SLR) has gained increasing attention, while Continuous Sign Language Recognition (CSLR) remains substantially more challenging than Isolated SLR (ISLR) due to the difficulty of accurately detecting sign boundaries within co...
The integration of large-scale renewable energy sources has increased the complexity of operation and maintenance in modern power systems, causing on-site substation operation and maintenance activities to exhibit stronger continuity and dynamics, an...
Detecting small objects in unmanned aerial vehicle (UAV) imagery remains a challenging task due to the limited target scale, cluttered backgrounds, severe occlusion, and motion blur commonly observed in dynamic aerial environments. This study present...
Unmanned aerial vehicle (UAV) imagery poses persistent challenges for object detection, including dense small objects, large-scale variation, cluttered backgrounds, and stringent localization requirements, where conventional two-stage detectors often...
Accelerometer sensors and artificial intelligence (AI) are reshaping automated behavior monitoring in precision livestock management, yet their joint deployment on extensive rangelands is constrained by energy and bandwidth budgets. Low-Power Long-Ra...
Continuous monitoring of the Stand-to-Sit (STS) transition serves as a critical indicator of lower-limb frailty in the elderly, for which millimeter-wave radar provides an ideal privacy-preserving, device-free sensing solution. However, robustly dist...
Continental shale reservoirs exhibit pronounced multi-scale heterogeneity, with reservoir quality governed by the interplay of lamina assemblages, bedding continuity, and lithological spatial variability. Conventional digital outcrop modeling (DOM) p...
‘Slide scanners’ are rapid optical microscopes equipped with automated and accurate x-y travel stages with virtual z-motion that cannot be rotated. In biomedical microscopic imaging, they are widely deployed to generate whole-slide images...
The manner of walking (gait) is a powerful biometric that is used as a unique fingerprinting method, allowing unobtrusive behavioral analytics to be performed at a distance without subject cooperation. As opposed to more traditional biometric authent...